On frequency tracking properties of a generalized adaptive notch filter

2006 ◽  
Author(s):  
M. Niedzwiecki
Keyword(s):  
Notch Filter ◽  
Frequency Tracking ◽  
Adaptive Notch Filter

scholarly journals A Novel Adaptive Frequency Estimation Algorithm Based on Interpolation FFT and Improved Adaptive Notch Filter

2017 ◽  
Vol 17 (1) ◽  
pp. 48-52 ◽  
Author(s):  
Ting-ao Shen ◽  
Hua-nan Li ◽  
Qi-xin Zhang ◽  
Ming Li
Keyword(s):  
Convergence Rate ◽  
High Frequency ◽  
Frequency Estimation ◽  
Notch Filter ◽  
Estimation Algorithm ◽  
Signal Frequency ◽  
Tracking Accuracy ◽  
Frequency Tracking ◽  
Adaptive Notch Filter ◽  
Fast Estimation

Abstract The convergence rate and the continuous tracking precision are two main problems of the existing adaptive notch filter (ANF) for frequency tracking. To solve the problems, the frequency is detected by interpolation FFT at first, which aims to overcome the convergence rate of the ANF. Then, referring to the idea of negative feedback, an evaluation factor is designed to monitor the ANF parameters and realize continuously high frequency tracking accuracy. According to the principle, a novel adaptive frequency estimation algorithm based on interpolation FFT and improved ANF is put forward. Its basic idea, specific measures and implementation steps are described in detail. The proposed algorithm obtains a fast estimation of the signal frequency, higher accuracy and better universality qualities. Simulation results verified the superiority and validity of the proposed algorithm when compared with original algorithms.

Minimal adaptive notch filter for respiratory frequency tracking

2003 ◽  
Author(s):  
E.G. Caiani ◽  
A. Porta ◽  
M. Terrani ◽  
S. Guzzetti ◽  
A. Malliani ◽  
...  
Keyword(s):  
Notch Filter ◽  
Respiratory Frequency ◽  
Frequency Tracking ◽  
Adaptive Notch Filter

A Frequency Tracking Method Based on Improved Adaptive Notch Filter for Coriolis Mass Flowmeter

2011 ◽  
Vol 128-129 ◽  
pp. 450-456 ◽  
Author(s):  
Hui Yue Yang ◽  
Ya Qing Tu ◽  
Hai Tao Zhang
Keyword(s):  
Absolute Convergence ◽  
Notch Filter ◽  
Superior Performance ◽  
Time Varying ◽  
Frequency Tracking ◽  
Adaptive Notch Filter ◽  
Mass Flowmeter ◽  
Coriolis Mass Flowmeter ◽  
Convergence Problems ◽  
Adaptive Notch Filters

Adaptive notch filters (ANF) are known have non-absolute convergence problems which will lead to precision reduction in long-playing frequency tracking. In this paper, we propose an improved ANF based on Steiglitz-McBride method (SMM) for Coriolis mass flowmeter (CMF) whose frequency, amplitude and phase are time-varying based on the random walk model. An monitor is designed to monitor whether the frequency is estimated rightly or the ANF just filters noise. If the frequency of CMF’s signal is missed, we will modify the parameters and restart the ANF to resume the search for the correct frequency again. The particular algorithm of the improved ANF is also put forward. Simulations have verified the effectiveness of the presented method in tracking CMF’s frequency, which shows superior performance comparing to the primary SMM based ANF.

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